class_docstr: Linformer encoder.
class_docstr_tok: ["Linformer","encoder","."]
code: def __init__(self, args, dictionary):
      super().__init__(args, dictionary)
      self.register_buffer("version", torch.tensor(2))
  
file_path: fairseq/examples/linformer/linformer_src/models/linformer_roberta.py
imports: import logging
  import torch
  from fairseq import utils
  from fairseq.models import register_model, register_model_architecture
  from fairseq.models.roberta import init_bert_params, roberta_base_architecture, roberta_large_architecture, RobertaEncoder, RobertaModel
  from fairseq.utils import safe_hasattr
  from ..modules.linformer_sentence_encoder import LinformerTransformerEncoder
label_desc: Use image node_id 1 to create a new LinformerEncoder object from inherited base classes: RobertaEncoder with example: obj = LinformerEncoder(args, dictionary)